Load forecasting models in smart grid using smart meter information: a review

F Dewangan, AY Abdelaziz, M Biswal - Energies, 2023 - mdpi.com
The smart grid concept is introduced to accelerate the operational efficiency and enhance
the reliability and sustainability of power supply by operating in self-control mode to find and …

A review of data-driven building energy consumption prediction studies

K Amasyali, NM El-Gohary - Renewable and Sustainable Energy Reviews, 2018 - Elsevier
Energy is the lifeblood of modern societies. In the past decades, the world's energy
consumption and associated CO 2 emissions increased rapidly due to the increases in …

Application of an artificial neural network to optimise energy inputs: An energy-and cost-saving strategy for commercial poultry farms

E Elahi, Z Zhang, Z Khalid, H Xu - Energy, 2022 - Elsevier
The current study estimates target values of energy inputs along with an assessment of
energy-and cost-saving strategies for poultry farms. In 2019, cross-sectional data were …

Forecast energy demand, CO2 emissions and energy resource impacts for the transportation sector

ME Javanmard, Y Tang, Z Wang, P Tontiwachwuthikul - Applied Energy, 2023 - Elsevier
Managing energy demand and reducing greenhouse gas emissions are among the most
significant challenges ahead for many countries. Accurate prediction of energy demand and …

[HTML][HTML] Trees vs Neurons: Comparison between random forest and ANN for high-resolution prediction of building energy consumption

MW Ahmad, M Mourshed, Y Rezgui - Energy and buildings, 2017 - Elsevier
Energy prediction models are used in buildings as a performance evaluation engine in
advanced control and optimisation, and in making informed decisions by facility managers …

A review on time series forecasting techniques for building energy consumption

C Deb, F Zhang, J Yang, SE Lee, KW Shah - Renewable and Sustainable …, 2017 - Elsevier
Energy consumption forecasting for buildings has immense value in energy efficiency and
sustainability research. Accurate energy forecasting models have numerous implications in …

Machine learning for estimation of building energy consumption and performance: a review

S Seyedzadeh, FP Rahimian, I Glesk… - Visualization in …, 2018 - Springer
Ever growing population and progressive municipal business demands for constructing new
buildings are known as the foremost contributor to greenhouse gasses. Therefore …

Forecasting methods in energy planning models

KB Debnath, M Mourshed - Renewable and Sustainable Energy Reviews, 2018 - Elsevier
Energy planning models (EPMs) play an indispensable role in policy formulation and energy
sector development. The forecasting of energy demand and supply is at the heart of an EPM …

Survey on multi-output learning

D Xu, Y Shi, IW Tsang, YS Ong… - IEEE transactions on …, 2019 - ieeexplore.ieee.org
The aim of multi-output learning is to simultaneously predict multiple outputs given an input.
It is an important learning problem for decision-making since making decisions in the real …

Forecasting energy use in buildings using artificial neural networks: A review

J Runge, R Zmeureanu - Energies, 2019 - mdpi.com
During the past century, energy consumption and associated greenhouse gas emissions
have increased drastically due to a wide variety of factors including both technological and …